Distributed lifecycle management for cloud platforms

ABSTRACT

An example system includes a number of nodes, each including a processor and a non-transitory machine readable medium storing a copy of an operating system image. Each copy of the operating system image may include a minimum set of artifacts of a cloud platform application, and lifecycle manager program instructions that, when executed by any of the nodes, instantiate a lifecycle manager for the respective node. The lifecycle manager may be configured to, in response to receiving a platform cluster creation request, automatically establish a cloud platform of the cloud platform application including the respective node as a sole member, and then invite others of the nodes to join the cloud platform. The lifecycle manager may also be configured to, in response to receiving an invitation to join an established cloud platform of the cloud platform application that was established by another one of the nodes, automatically integrate the respective node into the established cloud platform.

BACKGROUND

Cloud platforms may be used to provide cloud services to clients. Acloud platform is formed by a cloud platform application being run onunderlying hardware infrastructure. Cloud services include, for example,Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS),Infrastructure as a Service (laaS), and so on.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example of a deployed cloud platform.

FIGS. 2A-3C illustrate example cloud platforms at various stages ofdeployment. Specifically, FIG. 2A illustrates an initial deploymentstage in which the nodes are in a ready state. FIG. 2B illustrates asecond deployment stage, in which the cloud platform has one membernode. FIG. 2C illustrates a third deployment stage, in which a secondmember node has been integrated into the cloud platform. FIG. 3Aillustrates fourth deployment stage in which the cloud platform includesthree member nodes. FIG. 3B illustrates a fifth deployment stage inwhich the cloud platform includes more than three member nodes. FIG. 3Cillustrates a sixth deployment stage in which the cloud platformincludes N member nodes.

FIG. 4 is a process flow diagram illustrating an example process forinitial setup of a platform setup.

FIG. 5 is a process flow diagram illustrating an example process forintegrating into a cloud platform.

FIG. 6 is a process flow diagram illustrating an example process forresponding to a scaling event.

FIG. 7 is a process flow diagram illustrating an example process formaintaining a cloud platform.

FIG. 8 illustrates an example non-transitory machine readable mediumstoring example lifecycle manager program instructions.

DETAILED DESCRIPTION 1—Definitions

Could Platform. As used herein, a cloud platform is a distributedcomputing system (computing cluster) that is to dynamically providecloud services. The cloud platform is formed by a runtime instance of acloud platform application and underlying hardware infrastructure.

Could Platform Application. As used herein, a cloud platform applicationis a distributed application for establishing and managing a cloudplatform. As used herein, a distributed application is an applicationhaving components that can be run in a distributed manner on multiplenodes. Examples of commercially available cloud platform applicationsinclude Kubernetes, Mesos, and OpenStack.

Node. As used herein, a node is any computing device (virtualized orphysical) that includes at least one processor (virtualized or physical)capable of executing program instructions stored on a non-transitorymachine readable medium. A node may also include additional components(virtual or physical), such as memory (e.g., the aforementionednon-transitory machine readable medium), input/output units,controllers, peripherals, storage devices, etc. For example, a node maybe a virtual machine (VM), a server, a blade of a blade server system, acompute module of a composable infrastructure appliance, a compute nodeof a converged (or hyperconverged) appliance, a compute node of arack-scale system, a system-on-chip (SoC), a personal computer, aprinted circuit board containing a processor, etc. It is possible formultiple distinct physical nodes to be housed in the same chassis,although this need not necessarily be the case. It is also possible formultiple distinct nodes to share some or all of their components—forexample, virtual machines may be said to share the underlying physicalhardware from which the virtual machines are virtualized.

Artifact. As used herein, an artifact is any piece of digitalinformation that is part of or can be used by a computer program.Examples of artifacts include executable binary files, source files,scripts, tables, libraries, documents, and any other digital data.

Operating System Image. As used herein, an operating system image is animage (e.g., disk image) that includes artifacts to control operationsof a node.

Services. As used herein, a service is a functionality or group offunctionalities of a cloud platform. For example, services may includean API service, a domain name system service, a scheduler services, adistributed key value store service, a platform worker (aka slave orminion) service, and so on.

Role. As used herein, a role is a combination of services provided (orto be provided) by a node. Roles can be, but do not necessarily have tobe, specified by a particular name. Roles may be, but do not necessarilyhave to be, associated with a configuration management script, such asan Ansible playbook.

2—Deploying, Maintaining, and Changing a Cloud Platform

Lifecycle management of a cloud platform refers to any one of (or anycombination of) the functions of deploying, maintaining, and scaling acloud platform. Deploying, maintaining, and scaling a cloud platform canbe complicated and costly endeavors. In particular, many approaches todeploying, maintaining, and scaling a cloud platform, may requiresignificant time and effort of an IT professional (or a team ofprofessionals), which can result in high operation costs for the cloudplatform. For example, in many approaches to deploying a cloud platform,an IT professional with knowledge of the particular cloud platformapplication being used may be needed to design the overall configurationof the system (e.g., determine which roles or services the system needs,determine which nodes should be assigned which roles/services, determinewhich software to install on which nodes, etc.), and then configure eachnode in the system. As another example, in many approaches, day-to-daymaintenance tasks and failures require manual diagnosis and interventionby an IT professional. As another example, scaling the system afterinitial deployment is not supported in some approaches, or in otherapproaches is achieved via a manual reconfiguration of nodes by an ITprofessional.

Accordingly, disclosed herein are technologies that may simplify andreduce costs of deploying, maintaining, and scaling a cloud platform.For example, in examples described herein, a cloud platform may bedeployed by providing intelligent nodes that are able to automaticallyself-assemble into the desired platform, maintain the platform, anddynamically scale up or down the platform, with minimal manualintervention and without centralized top-down control. The nodes may be“intelligent” in that, among other things, they each may include anexample lifecycle management program (“LCM”) that automatically workswith the LCM's of the other nodes to cooperatively control thedeployment, maintenance, and scaling of the cloud platform.

Specifically, in some examples, the cloud platform may be deployed byproviding a set of the aforementioned intelligent nodes and instructingone of the nodes to begin self-assembling the platform. This first nodemay establish a cloud platform with itself as the sole member, andautomatically invite the other nodes into the platform. As each nodejoins the platform, its LCM may automatically determine how the nodeshould be configured to provide a best possible platform. In doing so,the LCMs of the nodes may coordinate with one another via a distributeddecision making process, to ensure that a desired overall configurationof the platform is achieved. For example, the LCMs may identify whichroles the platform currently needs based on a desired end-state (e.g., aspecified fault tolerance) and the currently available resources, andmay determine which nodes should play which roles. Each node may beprovisioned from the outset with an image containing all of theartifacts needed to establish a full-fledged cloud platform, andtherefore any of the nodes may be able to take on any needed role of thecloud platform. Each node's LCM may automatically configure its node toassume the role it has selected. Accordingly, the platform selfassembles by starting with one initial member node and growing andconfiguring and reconfiguring itself as the other nodes join. Thus, insome examples, no manual intervention is needed to deploy the platformapart from providing the resources (e.g., the nodes) for the system andinstructing one of the nodes to begin self-assembling the platform.

In addition, in some examples, once the cloud platform is deployed, theLCMs of the nodes may automatically perform maintenance for theplatform, including, for example, identifying and performing periodicplatform maintenance tasks, identifying and remediating failures, etc.For example, each node's LCM may monitor the status of the system, and,in response to a failure event (such as the failure of a service) thatmight require a remediation action (such as restarting the service onanother node), the LCMs of the nodes may decide via distributed decisionmaking which node should take the action. As another example, eachnode's LCM may monitor a platform maintenance task queue, and the LCMsof the nodes may decide via distributed decision making which nodeshould perform which platform maintenance task. Thus, in some examples,no significant manual intervention is needed for such maintenance of thesystem.

Furthermore, in some examples, the system may be easily scaled up ordown by adding or removing nodes from the system, with the LCMs of thenodes automatically determining how to configure (or reconfigure) thenodes in view of the changes. For example, each node's LCM may monitorfor the addition or removal of a node from the system, and, in responseto the removal or addition of a node, the LCMs of the nodes may decidevia distributed decision making how to configure or reconfigure thenodes in view of the change. Thus, in some examples, no significantmanual intervention is needed to scale the platform.

In examples described herein, the nodes form a cooperative system, inwhich control over the configuration of the system (both initial, andongoing) is distributed among the nodes (via their LCMs). This is incontrast to an alternative approach, in which configuration of the nodesis controlled in a top-down manner by a master entity, such as aconfiguration management master. Furthermore, as mentioned above, theexamples described herein provide for a system that is essentiallyself-deploying and self-sustaining, can dynamically scale up or down(from a single node to many nodes), and can tolerate the failure of anynode and remediate those failures without outside intervention.

3—Example Cloud Platform

FIG. 1 illustrates an example cloud platform 100. The example cloudplatform 100 is formed by a runtime instance of a cloud platformapplication 20, a distributed key value store (DKVS) 30, and a number ofnodes 40. The nodes 40 are communicably connected to one another bycommunications media and network devices (virtual or physical) (notillustrated). The nodes 40 cooperate to instantiate the runtime instanceof the cloud platform application 20 and the DKVS 30 by executingrespective program instructions associated therewith.

The cloud platform application 20 is a distributed application forestablishing a cloud platform (e.g., the cloud platform 100) from a setof resources (e.g., the nodes 40) and managing the platform. Because itis a distributed application, the cloud platform application 20 includesmultiple components that can be executed in a distributed manner bymultiple nodes 40 (however, this capability does not preclude the cloudplatform application 20 from also being run entirely by a single node40, as in the case of a cloud platform 100 with one member node 40). Thedistribution of components of the cloud platform application 20 acrossthe nodes 40 is illustrated conceptually in FIG. 1 by the cloud platformapplication 20 spanning the nodes 40. The components of the cloudplatform application 20 may include, for example, an API server, adomain name system service, a scheduler, a distributed key value storeserver (or proxy), a platform worker (aka slave or minion) service, etc.In a fully deployed platform 100, each component of the cloud platformapplication 20 is run by at least one of the nodes 40 that are part ofthe cloud platform 100, a component can be (but does not necessarilyhave to be) run by multiple nodes 40, and a node 40 can (but does notnecessarily have to) run the same components as other nodes 40. Anycloud platform application may be used as the cloud platform application20, including commercially available cloud platform applications such asKubernetes, Mesos, and OpenStack.

The DKVS 30 is a logical storage volume in which the nodes 40 can storekey-value pairs. The DKVS 30 is created and managed by a DKVSapplication (not illustrated) that is executed by the nodes 40. The DKVS30 is backed by storage volumes, such as respective storage volumes 43of the nodes 40 or storage volumes (not illustrated) external to thenodes 40 that are accessible to the nodes 40 over a network (notillustrated). The DKVS 30 may be used by the cloud platform 100 to, forexample, store and communicate: platform configuration information,platform health/status information, and a platform maintenance taskqueue. Any DKVS application may be used to establish the DKVS 30,including commercially available DKVS applications, such as etcd.

The nodes 40 may each include a processor 41, a memory 42, a storagevolume 43, a lifecycle manager (“LCM”) 500, local components of thecloud platform application 20, and local components of a DKVSapplication. The LCM 500 of a given node 40 may be formed by theprocessor 41 of that node 40 executing LCM program instructions 501,which will be described below with reference to FIG. 8. As noted above,the processor 41 of a given node 40 may also execute programinstructions of local components of the cloud platform application 20and may execute program instructions of local components of the DKVSapplication.

More specifically, each node 40 is a computing device (virtualized orphysical) that includes at least one processor 41 (virtualized orphysical) capable of executing instructions stored on a non-transitorymachine readable medium, such as memory 42 (virtualized or physical).The nodes 40 may also include a storage volume 43 (virtualized orphysical) that may persistently store data for the node 40. The nodes 40may also include additional components (virtual or physical), such asinput/output units, controllers, peripherals, storage devices, etc. Forexample, a node 40 may be a virtual machine (VM), a server, a blade of ablade server system, a compute module of a composable infrastructureappliance, a compute node of a converged (or hyperconverged) appliance,a compute node of a rack-scale system, a system-on-chip (SoC), apersonal computer, a printed circuit board containing a processor, etc.It is possible for multiple distinct physical nodes 40 to be housed inthe same chassis, although this need not necessarily be the case. It isalso possible for multiple distinct nodes 40 to share some or all oftheir components.

The processor 41 may include (or be virtualized from) any circuitrycapable of executing machine-readable instructions, such as a centralprocessing unit (CPU), a microprocessor, a microcontroller device, adigital signal processor (DSP), etc.

The memory 42 may include (or be virtualized from) any non-transitorymachine-readable medium from which the processor 41 can read programinstructions, including volatile media such as random-access-memory(RAM) (e.g., DRAM, SRAM, etc.) and/or persistent (non-volatile) mediasuch as non-volatile RAM (NVRAM) (e.g., flash memory, Memristor RAM,Resistive RAM, Phase Change Memory, 3D XPoint memory, etc.).

The storage volume 43 may include (or be virtualized from) any storagedevice that is capable of persistently storing digital data, such ashard disk drives, solid state drives (e.g., flash drives), magnetic tapedrives, optical disks, etc.

The nodes 40 may each be provisioned with a copy of an operating systemimage 400. The operating system image 400 may be stored, for example, inthe storage volume 43. Each copy of the operating system image 400 mayinclude at least all of the artifacts of the cloud platform application20 that are needed to establish a desired cloud platform 100 of thecloud platform application 20 (referred to herein as “the minimum set ofartifacts” for the cloud platform application 20). In other words, asingle node 40 provisioned with the minimum set of artifacts would beable to establish a fully functional cloud platform 100 having itself asthe sole member node 40. The artifacts may include, for example,executable binaries of the cloud platform application 20. The artifactsmay also include, for example, files, libraries, and other data of thecloud platform application 20. The operating system image 400 may alsoinclude additional artifacts of the cloud platform application beyondthe bare minimum needed to establish the cloud platform. In addition, insome examples, the operating system image 400 may include the LCMprogram instructions 501.

It should be understood that what constitutes the minimum set ofartifacts for a cloud platform 100 depends on the type of cloud platform100 that it is desired to establish. A cloud platform application 20 maybe capable of establishing multiple different types of cloud platforms100, and each may have its own minimum set of artifacts. Anadministrator or other management entity may determine a type of cloudplatform 100 that is desired and hence which artifacts are needed forthat cloud platform 100, for example as part of creating (or procuring)the operating system image 400.

In some examples, every software component of the cloud platformapplication 20 that is included in the operating system image 400 isincluded in an installed state, but may be quiesced until and unless itis needed. In some examples, a single cloud platform application 20 maybe able to form multiple types of cloud platforms (e.g., a containerbased SaaS platform, a VM based PaaS/laaS platform, etc.), in which casethe operating system image 400 may include artifacts for one, multiple,or all of the types of cloud platforms that the cloud platformapplication 20 can establish.

For example, if the cloud platform application 20 is Kubernetes, thenthe minimum set of artifacts that are needed to establish one exampletype of Kubernetes container-based cloud platform includes: a KubernetesAPI server component, a Kubernetes DNS component, a Kubernetes schedulercomponent, a Kubernetes Minion component, a container runtime interfacecomponent (e.g., Docker, runc, clear container, rkt), a registrycomponent (e.g., Docker Registry), an overlay network component (e.g.,flannel), and a computer operating system (e.g., a linux OS).

As another example, if the cloud platform application 20 is Mesos, thenthe minimum set of artifacts that are needed to establish one exampletype of Mesos container-based cloud platform includes: a mesos-mastercomponent, a mesos-agent component, a mesos-dns component, a schedulercomponent, a DKVS (e.g., zookeeper), a container runtime (e.g., Docker,runc, clear container, rkt), a java component, and a computer operatingsystem (e.g., a linux OS).

As another example, if the cloud platform application 20 is OpenStack,then the minimum set of artifacts that are needed to establish oneexample type of OpenStack VM vending cloud platform includes: nova stackcomponents (e.g., nova api, nova scheduler, nova compute, etc.), acinder component, a neutron component, and a keystone component.

The above described approach for using the same operating system image400 for all nodes 40 may be contrasted with an alternative approach, inwhich different components of a cloud platform application are providedon different nodes. For example, in most cloud platforms, differentservices of a cloud platform application are installed on differentnodes (for example, different nodes may be provisioned with differentoperating system images depending on their intended role). In otherwords, in the alternative approach, while each component of the cloudplatform application that is needed to establish a cloud platform ispresent somewhere in the system, not every node has every component.Thus, in contrast to the examples described herein, in such alternativeapproaches someone may need to spend time and effort in determining howmany of each role is needed, which nodes should play which roles, andwhich components should be installed on which nodes.

As noted above, each node 40 includes an LCM 500, which may be formed byrunning the LCM program instructions 501. The LCM program instructions501 may be stored in the node 40's storage volume 43 and loaded into thenode 40's memory 42 for execution. In some examples, the LCM programinstructions 501 are included in the operating system image 400 that isprovisioned to each node 40, in addition to the minimum set of artifactsfor the cloud platform application 20. The LCM 500 of each nodescontrols the initial deployment, scaling, and maintenance of the cloudplatform 100, as described in greater detail below.

As noted above, the nodes 40 may include some components (such as“processor”, “memory”, “storage volume”, etc.) that may be physical orvirtualized. Generally, for purposes of this disclosure, it does notmatter whether the component(s) are physical or virtualized.Accordingly, any references herein and in the appended claims to anycomponents of a node 40 that do not specify “physical” or “virtual”should be understood to admit both physical and virtualized types of thecomponents (in any combination). However, any virtualized component of anode 40 is necessarily virtualized from underlying physical hardware.Accordingly, the recitation herein or in the appended claims of a givencomponent of a node necessarily implies the presence somewhere in thesystem of physical hardware corresponding to the given component, withthe given component either being one-and-the-same as the correspondingphysical hardware or being virtualized from the corresponding physicalhardware. Note that there is not necessarily a one-to-one ratio betweenphysical hardware and the virtual components virtualized therefrom (onevirtual component may span multiple physical components or multiplevirtual components may share one physical component). Thus, for example,a recitation herein or in the appended claims such as “a systemcomprises a number of nodes that each include a processor” should beunderstood to mean at least that: (A) each node has either a physicalprocessor or a virtual processor, and (B) if any nodes include a virtualprocessor, then the system includes at least one physical processor (notnecessarily owned by any particular node) from which the virtualprocessor is virtualized.

4. Example Lifecycle Manager

The LCM 500 of a given node 40 may automatically work with the otherLCMs 500 of the other nodes 40 to automatically control the initialdeployment of a cloud platform 100, maintenance of the cloud platform100, and/or scaling of the cloud platform 100. These functions aredescribed separately below for ease of understanding, but it should beunderstood that in practice these may overlap and are not necessarilymutually exclusive. Example operations pertaining to these functions aredescribed below, and some of these are illustrated as process flowcharts in FIGS. 4-7. The LCM program instructions 501 includeinstructions that, when executed by a processor, cause the LCM 500 toperform the operations described below, including, for example,instructions corresponding to the operations shown in FIG. 4-7.

4.1 Initial Deployment of the Cloud Platform

The initial deployment of the cloud platform 100 begins by providing anumber of nodes 40, each having a copy of the operating system image 400and the LCM program instructions 501 (which may be part of the operatingsystem image 400). The nodes 40 may be placed in a ready state byinstantiating the LCM 500 of each node 40 (i.e., executing the LCMprogram instructions 501 on each node 40) and communicably connectingthe nodes 40 to one another. Once in the ready state, one of the nodes40 (hereinafter, “the first node 40-1”) may be instructed to start aprocess of creating the cloud platform 100, whereupon the nodes 40 startto self-assemble into the cloud platform 100.

When the nodes 40 are in the ready state, a platform creation request issent to the LCM 500 of the first node 40-1 (see FIG. 2A). In response,the first node 40-1 begins the self-assembly of the cloud platform 100,for example by executing operations such as those illustrated in FIG. 4.Specifically, the process illustrated in FIG. 4 may be performed by theLCM 500 of the first node 40-1 (i.e., the node 40 that receives aplatform creation request).

FIG. 4 will now be described. In block 601, LCM 500 receives a platformcreation request, for example from an administrator or other managemententity. The platform creation request includes at least an instructionto begin deployment of the cloud platform 100. The platform creationrequest may also include an identification of a resource envelope forthe cloud platform 100, such as, for example, an identification of theother nodes 40 that are to be part of the cloud platform 100. Theplatform creation request may also include some general platform-wideparameters, such as a target fault tolerance level. In some examples, itdoes not matter which one of the nodes 40 is chosen to receive theplatform creation request, since any one of the nodes 40 may be capableof handing the request (recall that all of the nodes 40 may beprovisioned with the same operating system image 400 including the LCMprogram instructions 501).

In response to receiving the platform creation request, in block 602 theLCM 500 creates the DKVS 30. For example, if using etcd as the DKVS 30,the first node 40-1 may establish an etcd cluster with itself as thesole member.

In block 603, the LCM 500 creates the cloud platform 100 with itself asthe sole member (see also FIG. 2B). For example, the LCM 500 of thefirst node 40-1 may establish the cloud platform 100 by automaticallyactivating (unquiescing) all of the local components of the cloudplatform application 20 needed for establishing the cloud platform 100and running local configuration scripts to automatically configureitself to take on all of the needed roles of the cloud platform 100.

In block 604, after establishing the cloud platform 100, the first node40-1 starts to invite the other nodes 40 that are supposed to be part ofthe cloud platform 100 (as identified, for example, in the platformcreation request) to join the platform 100. In particular, the firstnode 40-1 sends join platform requests to each of the nodes 40 that aresupposed to be part of the cloud platform 100 (see FIG. 2B). The joinplatform requests may include information needed for the nodes 40 to beable to join the cloud platform 100, such as, for example, anidentification of the DKVS 30 that the first node 40-1 created andcredentials for joining the DKVS 30 (if needed). Once the other nodes 40are part of the DKVS 30, they may have access to platform configurationinformation stored therein, which may be used by the nodes 40 to jointhe cloud platform 100. Additional details regarding these operationsare described below.

When one of the nodes 40 receives a join platform request, the LCM 500of the node 40 may automatically begin a process to integrate itselfinto the existing cloud platform 100 (i.e., join the platform 100 andconfigure itself to adopt a role therein), for example by executingoperations such as those illustrated in FIG. 5. Specifically, theprocess illustrated in FIG. 5 may be performed by the LCM 500 of anynode 40 that is not yet a member of the platform 100 that receives ajoin platform request.

FIG. 5 will now be described. In block 605, the LCM 500 receives thejoin platform request.

In block 606, in response to the join platform request the LCM 500 joinsthe DKVS 30 established by the first node 40-1.

Once a node 40 has joined the DKVS 30, the LCM 500 of the node 40 maythen obtain current platform configuration and status information fromDKVS 30, and the LCM 500 may determine how it should configure its node40 as part of joining the platform 100 in blocks 607-609

In particular, in block 607, the LCM 500 identifies a role that itthinks its node 40 should adopt in the cloud platform 100. For example,the LCM 500 may identify, based on the current state of the platform 100(as determined from the DKVS 30) and a desired configuration for theplatform 100, which role the node 40 should be configured to adopt so asto most improve the state of the cloud platform 100. Additional detailsof how a node 40 may identify such a role for itself are describedbelow.

In determining the role it should adopt, the LCM 500 uses the DKVS 30 tocoordinate with the other nodes 40 that are already members of theplatform 100 and/or other nodes 40 that are seeking to join theplatform. For example, in block 608, the LCM 500 determines whether alock in the DKVS 30 is available for the role, and adopts the role onlyif the lock is available. If the lock is not available, the LCM 500returns to block 607 to identify another role to perform. In someexamples, the LCM 500 may wait a predetermined amount of time beforeidentifying another role to perform.

In block 609, the LCM 500 obtains a lock for the role and thenconfigures itself to adopt the role. For example, the LCM 500 mayautomatically configure the node 40 to assume the identified role, forexample by running local configuration scripts to activate and configurethe services appropriate to the role (See FIG. 2C).

As nodes 40 newly join the platform 100, existing member nodes 40 of theplatform 100 may be aware of these events and may determine whether andhow they should reconfigure themselves in view of the new members. Theprocess of an existing member node 40 determining whether and how toreconfigure itself is described in greater detail below in relation toscaling.

Thus, the platform 100 begins with a single member—the first node40-1—and then grows as the other nodes 40 automatically integratethemselves into the platform 100. As nodes 40 continue to join the cloudplatform 100, they may each automatically determine how they should beconfigured based on the configuration of the other nodes 40. Existingmembers of the platform 100 may also automatically reconfigurethemselves if needed. Thus, the platform-level configuration of thecloud platform 100 may be automatically changed and updated asindividual nodes 40 join the platform 100, with the nodes 40 themselvesdetermining how they should be configured.

In both cases of newly joining nodes 40 and existing nodes 40reconfiguring themselves, the LCMs 500 of the nodes 40 may use the DKVS30 to obtain configuration information of other nodes 40, share theirown current and/or intended configuration, and otherwise coordinatetheir actions with the other nodes 40. For example, a distributedlocking mechanism of the DKVS 30 may be used by a node 40 to reserveavailable roles, services, or actions. Thus, the DKVS 30 may act as adistributed decision making mechanism, allowing the individual nodes 40to be independently in control of configuring themselves while alsocoordinating with one another to achieve a desired system-wideconfiguration.

For example, consider FIGS. 2A-3C, which illustrate example stages ofthe nodes 40 self-assembling into an example of the cloud platform 100.Although there is not necessarily a limit on the number ofroles/services in a cloud platform 100, for ease of description andunderstanding FIGS. 2 and 3 illustrate services associated with threeroles: hybrid manager-worker, manger-only, and worker-only. A hybridmanager-worker node 40 will have activated both services associated witha manager (hereinafter “manager services”) and services associated witha worker (hereinafter “worker services”). A manger-only node 40 willhave activated manager services but not worker services. A worker-onlynode 40 will have activated worker services but not manager services. InFIGS. 2 and 3, manager services are represented by boxes labeled“Manager Srvc” while worker services are represented by boxes labeled“Worker Srvc”. In the Figures, services that are not activated on a node40 (e.g., installed but quiesced services) are represented by boxes thathave dashed lines, while services that are activated are represented byboxes that have solid lines and no shading.

In FIG. 2A, a number of nodes 40 are provided that are to form theplatform 100. In the stage illustrated in FIG. 2A, each node 40 has arunning instance of the LCM 500 and the same components of the cloudplatform application 20 (e.g., Manager Srvc and Worker Srvc), which areall quiesced. In this state, the first node 40-1 is provided theplatform creation request, for example by a system administrator.

In FIG. 2B, in response to the platform creation request, the first node40-1 creates the platform 100 and DKVS 30 having itself as sole member.Because the first node 40-1 is the sole member of the platform 100 atthis point, it initially takes on all of the needed roles/services ofthe platform 100, which in this example means becoming a hybridmanager-worker. The first node 40-1 then sends the join platform requestto the other nodes 40.

In FIG. 2C, the second node 40-2 integrates itself into the system. Thesecond node 40-2 may determine that a desired configuration for theplatform 100 in this state is for the platform 100 to have one hybridmanager-worker node 40 and one worker-only node 40. Based on the desiredplatform-level configuration and the fact that there is already onehybrid manager-worker node 40 in the platform 100, the second node 40-2may determine that it should configure itself to be a worker-only node40. Thus, the second node 40-2 activates and configures the servicesassociated with a worker role.

In FIG. 3A, a third node 40-3 joins the cloud platform 100. Thethird-node 40-3 may determine that a desired platform-levelconfiguration for the platform 100 in this state is to have three hybridmanager-worker nodes 40 (e.g., to provide high availability). Based onthis desired configuration, the third node 40-3 may determine that itshould become a hybrid manager-worker, since this will improve theplatform 100 by bringing the platform 100 closer to the desiredconfiguration. In response, the second node 40-2 may also decide toreconfigure itself to become a hybrid manager-worker, to further improvethe platform 100 by bringing the platform 100 fully into the desiredconfiguration.

In FIG. 3B, a fourth node 40-4 joins the platform 100. The fourth node40-4 may determine that a desired platform-level configuration for theplatform 100 in this state is to have three hybrid manager-worker nodes40 and one worker-only node 40 (e.g., to provide high availability).Based on this desired configuration, the fourth node 40-4 may determinethat it should become a worker-only, since this will improve theplatform 100 by bringing the platform 100 closer to the desiredconfiguration.

The remaining nodes 40 may continue to join the platform 100, with eachdeciding how it should be configured, until all of the nodes 40 havebecome members of the platform. In some examples, the fourth andsubsequent nodes 40 may join as worker-only nodes 40. In some examples,as illustrated in FIG. 3C, when the platform becomes large enough (e.g.,the number of nodes 40 exceeds some threshold) or busy enough (e.g., ausage metric exceeds some threshold), the hybrid manger-worker nodes 40may be reconfigured to manager-only roles, as the management duties ofthese nodes 40 may be significant enough at this point to diminish theirability to also provide worker services.

4.2 Scaling of the Cloud Platform

Scaling of the cloud platform 100 means adding nodes 40 to or removingnodes 40 from the cloud platform 100. A portion of the initialdeployment of the platform 100 includes a scaling process, becauseduring initial deployment, the platform 100 scales from one initialmember to eventually include all of the originally deployed nodes 40.However, scaling can also occur after initial deployment, as new nodes40 are added beyond those initially deployed. In addition, scaling alsocovers the removal of nodes 40 from the platform 100, which generallydoes not occur as part of initial deployment. Hereinafter, a node beingadded to (or attempting to join) the platform 100 and a node 40 beingremoved from (or attempting to leave) the platform 100 are referred togenerally as “scaling events” when it is not important to distinguishbetween them.

To add a node 40 to (or integrate a node 40 into) the platform 100, thenode 40 must first be provisioned, for example by an administrator orother management entity, with the provisioned node 40 having an instanceof the LCM 500 running thereon and a copy of the operating system image400. Once the node 40 has been provisioned, the rest of the process ofadding the node 40 into the platform may be handled automatically by thenodes 40 with no or very minimal manual intervention. For the new node40 to be able to join the platform 100, the new node 40 and/or thecurrent member nodes 40 need to be made aware of one another. In someexamples, this may be accomplished automatically; for example, theplatform 100 may have a periodic maintenance task to check for updatesto its resource envelope (e.g., new nodes 40), which may reveal thepresence of the new node 40. In other examples, the administrator orother management entity may send a message to the platform 100 to notifyit of the new node 40. In response to detecting the presence of a newnode 40, one of the member nodes 40 may send the new node 40 a joinplatform request, just like the join platform requests that weredescribed above in relation to initial deployment. In response to thejoin platform request, the new node 40 may then attempt to join theplatform 100 in the same manner as a node 40 would join the platformduring initial deployment and as described in greater detail below.

Removing a node 40 from the platform may occur in many ways, includingintentionally and accidentally. For example, a node 40 may be removedfrom the platform by an administrator or other management entity sendinga command to the to-be-removed node 40 and/or to the other nodes 40 ofthe platform indicating that the to-be-removed node 40 is to be removedfrom the resource envelope of the platform 100 (hereinafter, “gracefulremoval”). In response to such a message, the remaining nodes 40 of theplatform 100 may enact processes to handle the removal of the node 40,including, for example, determining whether any of the remaining nodes40 need to reconfigure themselves, transferring load from theto-be-removed node 40 to other nodes, and so on. As another example, anode 40 may be removed from the platform 100 without necessarilynotifying the other nodes 40 in advance. For example, the node 40 may besuddenly shut down (intentionally or by a failure). As another example,the node 40 may experience a failure or error that, while not shuttingdown the node 40 completely, prevents the node from functioning as aplatform 100 member. As another example, the node 40 may be suddenlydisconnecting from the other nodes 40 (intentionally or by a failure).

When a scaling event occurs, this may have important implications forboth the node 40 that is the subject of the scaling event and the othernodes 40 that are members of the platform 100. In particular, a node 40that is to be added to the platform 100 may need to automaticallyconfigure itself as part of integrating into the platform 100, asdescribed in greater detail below. In addition, existing member nodes 40of the platform 100 that are not the subject of the scaling event mayalso need to reconfigure themselves in view of the scaling event. Inparticular, when a node 40 newly joins or leaves the platform 100, thismay bring the platform 100 into a state in which its currentconfiguration is not the desired configuration, and therefore one ormore existing members of the platform 100 may need to reconfigure itselfin order to bring the platform 100 as a whole into (or closer to) thedesired configuration.

Accordingly, the nodes 40 that are currently members of the platform 100need to be aware of such scaling events, so that they can determinewhether, and if so how, they should reconfigure themselves. Thus, insome examples the LCM 500 of each node 40 in the platform 100 may beconfigured to monitor for the addition or removal of nodes 40.Specifically, the LCM 500 of each node 40 that is a member of theplatform 100 may be configured to automatically monitor the status(e.g., health and configuration) of the platform 100, includingmonitoring which nodes 40 are members of the platform 100 (and theirhealth status) and which nodes 40 are attempting to join the platform100. The LCM 500 may find this information, for example, in the DKVS 30.The LCM 500 may also take other active steps to ascertain thisinformation, such as exchanging messages with other nodes 40. Based onthe status information, the LCM 500 of each node 40 in the platform 100may be configured to detect when nodes 40 join or leave platform 100. Inresponse to detecting such an event, each member node 40 may determinewhether it needs to reconfigure itself to account for the change.

In some examples, all of the nodes 40 monitor for scaling eventsconcurrently. In other examples, monitoring for scaling events is aperiodic maintenance task that is performed by one node 40 at a time. Insome examples, different types of scaling events may be monitored indifferent ways; for example, the adding of a node 40 and the gracefulremoval of a node 40 may be monitored as period maintenance tasksperformed by one node 40 at a time, while sudden failure of a node 40(e.g., shut down, disconnection, or other failure) may be monitored forby all nodes 40 concurrently.

4.2.1—Configuration of Nodes in Response to Scaling Events

As noted above, when a scaling event occurs, both the node 40 that isthe subject of the scaling event and the member nodes 40 of the platformmay need to configure themselves. In particular, when a node 40 newlyjoins (or attempts to join) the platform 100 (whether as part of initialdeployment, or subsequent to deployment), the newly joining node 40automatically configures itself, as described in greater detail below.In addition, existing members of the platform 100 may or may not need toreconfigure themselves in view of the newly joining node 40, dependingon the current configuration of the platform 100. When a node 40 leavesthe platform 40, the leaving node 40 does not necessarily need to do anyconfiguration (it may be, for example, simply shut down), but theexisting members of the platform 100 may or may not need to reconfigurethemselves in view of the changed number of nodes 40 in the platform100.

As describe above in relation to FIG. 5, the LCM 500 of a node 40 thatis newly joining the platform 100 may determine how to configure itselfbased on its identification of a role that it should play in theplatform 100. For example, the LCM 500 of the joining node 40 mayidentify the role to adopt based on what would improve the platform 100in view of its current configuration. For example, the LCM 500 of thejoining node 40 may identify a desired configuration of the platform 100as a whole in view of current conditions, and select a role that willbring the platform 100 into (or closer to) the desired configuration. Inparticular, the LCM 500 of the joining node 40 may identify a desiredconfiguration of a platform that has a number of nodes 40 equaling thesum of the nodes 40 currently in the platform 100 plus the joining node40 plus (in some examples) other concurrently joining nodes 40. As usedherein, a desired configuration of the platform 100 is a specificationof per-node 40 roles to be included in the platform 100 based on anumber of nodes 40, without necessarily specifying which particularnodes 40 adopt which particular roles. For example, a desiredconfiguration of the platform 100 may be “one hybrid manager-worker node40” for a one-node platform 100, “one hybrid manager-worker node 40 andone worker-only node” for a two-node platform 100, “three hybridmanager-worker nodes 40” for a three-node 40 platform 100, and so on(see Table 1 below for further examples). The LCM 500 of the joiningnode 40 may identify one of the roles in the identified desiredconfiguration of the platform 100 as the role it will adopt. In someexamples, the LCM 500 of the joining node 40 may attempt, when possible,to adopt one of roles of the desired configuration that is not yetprovided by the member nodes 40 of the platform 100.

The process for a current member node 40 of the platform 100 todetermine whether, and if so how, it should reconfigure itself inresponse to a scaling event may be similar to how a newly joining node40 determines how to configure itself. For example, the LCM 500 of acurrent member node 40 may execute operations such as those illustratedin FIG. 6.

In block 610, the current member node 40 detects a scaling event, suchas the addition or removal of a node 40 to/from the platform 100. Forexample, the LCM 500 of each node 40 may detect that a node 40 has newlyjoined (or is attempting to newly join) the platform 100 or that a node40 has been removed (or is going to be removed) from the platform 100 bymonitoring the DKVS 30. As another example, the member nodes 40 of theplatform 100 may monitor the status (e.g., health, connectivity, etc.)of other member nodes 40 so that they can detect the removal of a node40. In some examples, the member nodes 40 of the platform 100 may detectthe scaling event while the scaling event is ongoing (e.g., while a node40 is in the process of joining the platform 100). In other examples,the member nodes 40 of the platform 100 may detect the scaling eventafter the scaling event has finished (for example, as part of a periodicmaintenance task).

In blocks 611-615, the LCM 500 of the member node 40 determines whetherit should reconfigure itself in response to the scaling event, and if sohow. In some examples, the member nodes 40 of the platform 100 maydetermine whether/how they should reconfigure themselves while thescaling event is ongoing—for example, current member nodes 40 andjoining nodes 40 may configure/reconfigure themselves concurrently. Inother examples, the member nodes 40 of the platform 100 may determinewhether/how they should reconfigure themselves after the scaling eventhas finished—for example, joining nodes 40 may configure themselvesfirst, and then after this the current member nodes 40 may determinewhether any reconfiguration is needed.

In particular, in block 611, the LCM 500 determines a desiredconfiguration for the platform 100 in view of the number of nodes 40that will be members of the platform 100 as a result of the scalingevent. More specifically, in examples in which block 611 is performedafter the scaling event is finished, then the desired configuration isbased on the total number of nodes 40 currently in the platform 100(which would automatically include any nodes 40 that joined as part ofthe scaling event and exclude any nodes 40 that left as part of thescaling event). In examples in which block 611 is performed while thescaling event is ongoing, then the desired configuration is based on thetotal number of nodes 40 currently in the platform 100 plus any joiningnodes 40 and minus any leaving nodes 40. Because each node 40's LCM 500has the same logic, each LCM 500 will identify the same desiredconfiguration given the current state of the platform 100. More detailedexamples of how a desired configuration may be determined are describedbelow.

In block 612, the LCM 500 may determine whether any current member node40 of the platform 100 would need to be reconfigured in order for theplatform 100 to be in the desired configuration after the scaling event.For example, the configuration of current member nodes 40 may becompared to the desired configuration to identify any differencesbetween them. If there are no differences between the desiredconfiguration and the current platform 100 configuration, then noreconfiguration of member nodes 40 is needed. If the current platform100 configuration is a subset of the desired configuration (i.e., thecurrent configuring is missing one or more roles but there are noextraneous roles in the current configuration, relative to the desiredconfiguration) then no reconfiguration of member nodes 40 is needed,since the newly joining nodes 40 may be able to fulfill the missingroles. If the current platform configuration includes extraneous roles,then reconfiguration of member nodes 40 is needed to remove theextraneous roles (and also fill a missing role).

In some examples, it can be determined in advance which statetransitions of the platform 100 the LCM 500 would requirereconfiguration of member nodes 40 and which would not. For example,assuming the example desired configurations of Table 1 (describedbelow), then reconfiguration of member nodes is only required when thenumber of nodes 40 in the platform 100 transitions from two or less tothree or more and vice versa, or when the number of nodes 40 transitionsfrom X-1 or less to X or more and vice versa, where X is a specifiedthreshold. In such examples, the LCM 500 may determine whetherreconfiguration of member nodes 40 is required simply by determiningwhether the state transition that has occurred (or is occurring) as aresult of the scaling event is one of a list of specified statetransitions that require reconfiguration.

In block 612, in some examples, the process continues to block 613 if atleast one member node 40—any node 40—would need to be reconfigured; ifno member nodes 40 would need to be reconfigured, then the process mayend and the member node 40 may keep its current configuration. In otherexamples, the process continues to block 613 if one of the extraneousroles in the current configuration of the platform matches the currentrole of the member node 40 of the LCM 500 performing the process;otherwise the process ends for that node 40.

In block 613, the LCM 500 identifies a needed role for its node 40. Inparticular, the LCM 500 of each member node 40 may identify one of theroles specified in the desired configuration as the role it will adopt.

To ensure that the desired configuration is adopted in the platform 100in response to a scaling event, the nodes 40 may coordinate with oneanother via the DKVS 30 in their selection of roles. For example, thenodes 40 may use a distributed locking mechanism of the DKVS 30 todistribute the roles amongst themselves. For example, each type of role(e.g., hybrid manager-worker, manager-only, worker-only, etc.) may beallocated a specific number of locks in the distributed lockingmechanism corresponding to the number of that type of role that isspecified in the desired configuration. In such an example, a node 40must first reserve a lock for a role before configuring itself to adoptthe role, and may not adopt a role for which it has not reserved a lock.Thus, in this example, each current member node 40 and each newlyjoining node 40 (if any) may select its role by reserving a lockassociated with that role. This may ensure that all of the roles of thedesired configuration are ultimately filled.

Accordingly, in block 614 the LCM 500 may attempt to obtain a lock forthe role it has selected, and in so doing the LCM 500 determines whetheror not the lock is available. If the lock is available, then the processcontinues to block 615. If the lock is not available, then the processloops back to block 613, where the node 40 selects another role forwhich it can attempt to obtain a lock. In some examples, the LCM 500 maywait a predetermined amount of time before returning to block 613. Forexample, if there are five worker-only roles in the desiredconfiguration, and four nodes 40 have already obtained locks forworker-only roles, then a next (fifth) node 40 to try to obtain a lockfor the worker-only role would find the lock available while a following(sixth) node 40 to try to obtain a lock for the worker-only role wouldfind the lock unavailable. In some examples, nodes 40 that are notparticipating in reconfiguration (e.g., nodes 40 that answered “No” inblock 612) may automatically obtain (or keep, if they already have it) alock for their current role before other nodes 40 attempt to lock inroles, while nodes 40 that are participating in reconfiguration (e.g.,nodes 40 that answered “Yes” in block 612) may relinquish any lock ontheir current role before the nodes 40 attempt to lock in new roles.

In some examples, current member nodes 40 may be biased to seek to keeptheir currently configured roles if the role is one that is found in thedesired configuration and if a lock is available for it. In other words,a current member node 40 may first attempt to reserve a lock for itscurrently configured role, and may consider other roles only when thereare no locks remaining for its current role. This may help to reduceunnecessary changing of roles among member nodes 40, which may affectperformance of the platform 100. In addition, in some examples in whichmember nodes 40 determine whether/how to reconfigure themselvesconcurrently with joining nodes 40 determining how to configurethemselves, current member nodes 40 may be given priority over newlyjoining nodes 40 in reserving locks (e.g., all member nodes 40 selecttheir locks before joining nodes 40 are allowed to select locks), whichmay help to prevent newly joining nodes 40 from unnecessarily forcing acurrent member node 40 to change roles.

In block 615, the node 40 obtains the available lock for the role,whereupon the node 40 starts a process of automatically reconfiguringitself to adopt the role, for example by executing automatedconfiguration scripts associated with the role.

Although the description above occasionally focuses on examples in whicha single node 40 is joining or leaving the platform 100 at a time, itshould be understood that, in some examples, multiple nodes 40 may joinor leave the platform 100 at the same time. In particular, indetermining the desired configuration for the platform 100 as part ofdetermining what role to adopt, each node 40 may consider not justitself and the current member nodes 40, but also all of the nodes 40that are concurrently joining the platform 100. For example, if twonodes 40 are currently members of the platform and two more nodes 40 aretrying to join the platform simultaneously, all of these nodes 40 maydetermine a four-node desired configuration (two current members plustwo joining).

4.2.2—Desired Configurations of the Platform

As described above, in some examples the LCM 500 may need to determine adesired configuration of the cloud platform 100 as part of determininghow to configure or reconfigure itself. In such examples, the desiredconfiguration of the cloud platform 100 may depend on the number ofnodes 40 that are or will be in the platform 100 as a result of ascaling event. For example, a one-node 40 desired configuration differsfrom a two-node desired configuration, which differs from a three-node40 desired configuration, and so on. In some examples, the desiredconfiguration of the cloud platform 100 further depends on platform 100wide parameters, such as a desired fault tolerance. For example, athree-node 40 desired configuration with a specified fault tolerance ofone node may differ from a three-node 40 desired configuration with nospecified fault tolerance.

In some examples, each LCM 500 may identify a desired configuration bysearching a list of pre-specified desired configurations. The list maybe included in the LCM program instructions 501 of each node 40, and maybe indexed (i.e., keyed) at least based on a number of nodes 40. Inother examples, the LCM 500 of each node 40 may include logic fordetermining desired configurations on-the-fly based at least on a numberof nodes 40.

In examples in which the LCM program instructions 501 include a list (orlists) of pre-specific desired configurations, the list may take anyform, such as tables, arrays, associative lists, key-value stores, etc.As noted above, the list may be indexed at least by a number of nodes40. For example, the LCM 500 may search such a list to find the desiredconfiguration that is associated with a node number equal to the numberof nodes 40 currently in the platform 100 plus any nodes 40 currentlyattempting to join the platform 100 minus any nodes 40 currentlyattempting to leave the platform 100. In addition, the list may also beindexed by specified platform-wide configuration parameters (such as atarget fault tolerance), and/or any other parameter. In examples inwhich the indexing includes specified target platform configurationparameters, these may be specified, for example, to the first node 40-1in the platform creation request, and the first node 40-1 may recordthis information in the DKVS 30 from which subsequent nodes 40 mayobtain the information.

Table 1 illustrates one possible example of a list of desiredconfigurations for the platform 100 indexed by the number of nodes. Inthe example list of Table 1, it is assumed that it is desired to havehigh availability with a fault tolerance of one (for example, this maybe specified as a target configuration parameter), and that thereforehaving at least three manager roles is desired when possible. In theexample list of Table 1, it is also assumed that it is desirable to havea lowest number of manager roles, subject to the aforementionedconstraint of maintaining high availability if possible. In the examplelist of Table 1, it is also assumed that it is desirable to have nodes40 that perform manager services also perform worker services (i.e., behybrid manager-workers) until a size of the system becomes too large(e.g., the number of nodes 40 exceeds a specified threshold number ofnodes 40, denoted X in the Table) (see also FIG. 3C).

TABLE 1 Number of Hybrid Manager- Nodes Workers Workers-onlyManagers-only 1 1 0 0 2 1 1 0 3 3 0 0 4 3 1 0 5 3 2 0 6 3 3 0 . . . . .. . . . . . . X − 1 3 X − 4 0 X 0 X − 3 3 X + 1 0 X − 2 3 . . . . . . .. . . . .

In examples in which the LCM 500 of each node 40 determines desiredconfigurations on-the-fly rather than by consulting a pre-specifiedlist, the LCM 500 may include logic for making such determinations. Thelogic may include specified rules that may be applied in view of inputparameters, such as a number of nodes 40, to derive a desiredconfiguration of the platform 100. For example, the logic may include arule to include just one manager role when high availability is notrequired or is not possible. As another example, the logic may include arule to include exactly the minimum number of manager roles that arenecessary for high availability when high availability is specified andpossible. As another example, the logic may include a rule to alwayshave manager services be implemented in hybrid manager-worker nodes 40until a size of the platform 100 cross a specified threshold (e.g., thenumber of nodes meets/exceeds a threshold X), or until a performance ofthe manager nodes 40 drops below a specified threshold, or a load on thesystem becomes large enough.

4.3—Maintenance of the Cloud Platform

The LCM 500 of each node 40 in the platform 100 may automaticallyperform maintenance tasks for the platform. As used herein, “maintenancetasks” includes both planned maintenance tasks that arise according to aspecified schedule (e.g., periodic maintenance tasks) as well asreactionary maintenance tasks that arise in response to unplannederrors, failures, or other conditions.

In particular, the LCMs 500 may use the DKVS 30 to coordinate, viadistributed decision making, which nodes 40 will perform whichmaintenance tasks. For example, when an LCM 500 believes that amaintenance task needs to be performed and that it is able to performit, the LCM 500 may attempt to acquire a lock for the task in the DKVS30, to ensure that the task is not already being performed by anothernode 40. If the LCM 500 is able to obtain the lock, then it goes aheadand performs the task. In the case of planned or periodic maintenancetasks, in some examples each of the LCMs 500 may be aware when such atask should be performed based on a schedule specified in the LCMprogram instructions 501. In the case of unplanned tasks (e.g.,remediation of errors, failures, other conditions), the condition givingrise to the task may be detected by any one of the LCMs 500 bymonitoring the status of the platform 100. As used herein, the status ofthe platform 100 may include both the configuration of the platform 100(e.g., how many nodes, what roles the nodes are assigned, what servicesare activated and on which nodes, etc.), and the health of the platform100 (e.g., are any nodes or services experiencing errors or failures orotherwise unhealthy).

For example, the LCMs 500 may execute the example operations illustratedin FIG. 7.

In block 616, the LCM 500 determines whether a maintenance task (plannedor reactionary) needs to be performed. In particular, the LCMs 500 maydetermine whether maintenance tasks need to be performed by monitoring atask schedule or queue and/or monitoring the status of the platform 100.For example, the LCMs 500 may determine whether planned maintenancetasks need to be performed by monitoring a schedule of tasks specifiedin the LCM program instructions 501 and/or a task queue maintained inthe DKVS 30. In addition, the LCMs 500 may determine whether reactionarymaintenance tasks need to be performed by monitoring the status of theplatform 100. For example, the LCM 500 may periodically decide, based ona current state of the platform 100, whether there any actions thatcould be taken to improve the state of the platform 100. If there issuch an action, then the LCM 500 may consider the action to be amaintenance task that needs to be performed. Detecting actions thatcould improve the platform may include detecting errors, failures, orother conditions that adversely affect the platform 100 and, if such acondition is detected, automatically determining whether an action canbe taken to remediate (fully or partially) the condition. When the LCM500 has identified a maintenance task that needs to be performed, theLCM 500 proceeds to block 617.

For example, suppose that a service on a node 40 experiences an error orfails completely. Such an occurrence may be detected by the LCM 500 ofanother node 40 as a condition for which remedial action is warranted,and the detecting LCM 500 may then determine an action that wouldimprove the platform 100 (i.e., remediate the failure), such as activinganother instance of the failed service on another node 40. Thus, the LCM500 may identify activing another instance of the failed service as amaintenance task that needs to be performed, and may proceed to block617 on this task.

As another example, suppose that an entire node 40 fails or is otherwisedisconnected from the rest of the platform. Such an occurrence may bedetected by the LCM 500 of another node 40 as a condition for whichremedial action is warranted, and the detecting LCM 500 may thendetermine an action that would improve the platform 100 (i.e., remediatethe failure), such as a member node 40 reconfiguring itself to aspecific role and/or taking on a portion of the load previously servicedby the failed node 40. Thus, the LCM 500 may identify reconfiguring intothe specified role as a maintenance task that needs to be performed, andmay proceed to block 617 on this task. The LCM 500 may also identifytaking on a portion of the load previously serviced by the failed node40 as another maintenance task that needs to be performed, and mayproceed to block 617 on this task. Note that this example overlaps withthe scaling function described above, since the failure of a node 40 isone example of a scaling event. In other words, in some circumstances,identifying a scaling event and determining that reconfiguration isneeded in response to the scaling event (see blocks 610-613 of FIG. 6)can be an example of determining that a maintenance task needs to beperformed (block 616 of FIG. 7).

As another example, a periodic maintenance task may includeinterrogating an inventory discovery source to see if changes have beenmade to the inventory or resource envelope of the platform 100. The LCM500 of each node 40 may be aware when this periodic task should beperformed, for example by consulting a task schedule. When the time forperforming the task arrives, the first one of the LCMs 500 to noticethis fact may determine that the maintenance task needs to be performedand may proceed to block 617.

In block 617, the LCM 500 determines whether a lock is available in atask queue of the DKVS 30 for the task that was identified in block 616.This may be done to ensure that multiple nodes 40 do not attempt toperform the same task at the same time. In some examples, the taskidentified in block 616 may not yet be listed in a task queue of theDKVS 30 (for example, if the LCM 500 was the first to identify areactionary task), in which case the determining whether a lock isavailable may include posting the maintenance task to the task queue inthe DKVS 30. If the task has already been reserved by another node 40(i.e., the lock is unavailable), the LCM 500 may return to block 616 tocontinue monitoring for other maintenance tasks. In some examples, theLCM 500 may wait a predetermined amount of time before returning toblock 616. If the lock is available, then the LCM 500 may continue toblock 618.

In block 618, the LCM 500 obtains a lock for the maintenance task, andthen performs the task. It should be understood that, in some examples,determining whether a lock is available and obtaining the lock may beperformed as part of the same operation—for example, it may bedetermined whether a lock is available by attempting to obtain the lock,with the attainment of the lock indicating that the lock was availableand the inability to attain the lock indicating that the lock was notavailable.

In some examples, in block 616 or 617 the LCM 500 may also determinewhether its node 40 would be able to perform the task. For example, anode 40 may not be able to perform a task if it is too busy, does nothave authorization, etc. If the node 40 is able to perform the action,then LCM 500 may continue to block 617 or 618 as described above. If,however, the node 40 is not able to perform the action, then the LCM 500may loop back to block 616 and monitor for other tasks without obtaininga lock or performing the task. In some examples, even if the node 40 isnot able to perform the task, the LCM 500 may still check the DKVS 30 inblock 617 to verify that the task is included in the task queue, and ifnot the LCM 500 may post the task to the task queue.

In block 616, in some circumstances, the LCM 500 may determine that anaction cannot be taken to remediate an identified condition. Forexample, the LCM 500 may be unaware of any remedial action for thecondition. As another example, the LCM 500 may be aware of a remedialaction but the remedial action may not currently be possible in view ofthe current state of the platform 100. In some examples, when the LCM500 determines that an action cannot be taken to remediate a condition,then the LCM 500 does not identify a maintenance task.

In some examples, when an LCM 500 identifies that an action can be takenthat would remediate an identified condition, in some circumstances theLCM 500 may simply perform the action on its own initiative rather thanattempting to obtain a lock to perform an action. In particular, someactions that are not rivalrous may be performed without needing toobtain a lock in the DKVS 30. In this context, an action is notrivalrous if it is acceptable for more than one of the nodes 40 toperform the action. Because non-rivalrous actions can (and in somecases, should) be performed by multiple nodes 40, there is no need toreserve the action for one node 40 via a locking mechanism. An exampleof a not rivalrous action is a node 40 reconfiguring one or more of itsown services to reflect a change in another service on another node 40,such as a change in the location of another service (some servicesdepend on location and configuration of other services). Such an actionis not rivalrous because it is acceptable (in some cases, desirable) forevery node 40 to reconfigure its own services in response to such anevent.

5—Example Processor Executable Instructions

FIG. 8 illustrates example processor executable instructions stored on anon-transitory machine readable medium 5000. In particular, lifecyclemanager (LCM) program instructions 501 are stored on the medium 5000.

The LCM instructions 501 may include instructions that, when executed,instantiate the LCM 500 described above. In particular, the LCMinstructions 501 may include instructions to perform any or all of theoperations that were described above as being performed by the LCM 500,including, for example, any of the example operations illustrated inFIGS. 4-8.

For example, the LCM instructions 501 may include initial setupinstructions 502, integration instructions 503, scaling instructions504, and maintenance instructions 505. The initial setup instructions502 may include instructions to perform the operations of FIG. 4. Theintegration instructions 503 may include instructions to perform theoperations of FIG. 5. The scaling instructions 504 may includeinstructions to perform the operations of FIG. 6. The maintenanceinstructions 505 may include instructions to perform the operations ofFIG. 7.

For example, the initial setup instructions 502 may include instructionsto the cause a node 40 to, in response to receiving a platform clustercreation request, automatically: establish a cloud platform 100including the node 40 as a member; and invite other nodes 40 to join thecloud platform 100. In some examples, the establishing of the platform100 includes automatically establishing a distributed key value clusterfor communicating a state of the platform 100 among the nodes 40.

For example, the integration instructions 503 may include instructionsto cause a node 40 to, in response to receiving an invitation to join acloud platform 100, automatically integrate the respective node 40 intothe cloud platform 100. In some examples, the automatically integratingthe respective node 40 into the cloud platform 100 includesautomatically joining a distributed key value cluster associated withthe cloud platform 100. In some examples, the automatically integratingthe respective node 40 into the cloud platform 100 includesautomatically determining which services of the cloud platform 100 toactivate on the respective node 40 based on a current configuration ofthe cloud platform 100. In some examples, the determining which servicesof the cloud platform 100 to activate on the respective node 40 includesautomatically: identifying a role for the respective node 40 based onthe current configuration of the second cloud platform 100, andselecting for activation those services of the cloud platform 100 thatare associated with the identified role.

For example, the scaling instructions 504 may include instructions tocause a node 40 to, in response to detecting a change in a configurationof the cloud platform 100, automatically: determine whether changing arole of the respective node 40 would improve the configuration of theplatform 100, and, in response to determining that changing the role ofthe respective node 40 would improve the configuration of the platform,attempt to change the role of the respective node 40.

For example, the maintenance instructions 505 may include instructionsto cause a node 40 to monitor a status of the platform 100, based on thestatus, determine whether there is an action that would improve thestatus of the platform 100, and in response to identifying an actionthat would improve the status of the platform 100, attempt to performthe action. In some examples, the maintenance instructions 505 mayinclude instructions to cause a node 40 to, in response to detecting achange in a health of a given service of the platform 100, automaticallydetermine whether the respective node 40 should activate the givenservice. In some examples, the maintenance instructions 505 may includeinstructions to cause a node 40 to automatically: monitor a platformtask list of the platform 100 for maintenance tasks that need to beperformed, and in response to identifying a maintenance task that needsto be performed, attempt to perform the maintenance task.

6—Other Definitions

As used herein, to “provide” an item means to have possession of and/orcontrol over the item. This may include, for example, forming (orassembling) some or all of the item from its constituent materialsand/or, obtaining possession of and/or control over an already-formeditem.

Throughout this disclosure and in the appended claims, occasionallyreference may be made to “a number” of items. Such references to “anumber” mean any integer greater than or equal to one. When “a number”is used in this way, the word describing the item(s) may be written inpluralized form for grammatical consistency, but this does notnecessarily mean that multiple items are being referred to. Thus, forexample, a phrase such as “a number of active optical devices, whereinthe active optical devices . . . ” could encompass both one activeoptical device and multiple active optical devices, notwithstanding theuse of the pluralized form.

The fact that the phrase “a number” may be used in referring to someitems should not be interpreted to mean that omission of the phrase “anumber” when referring to another item means that the item isnecessarily singular or necessarily plural.

In particular, when items are referred to using the articles “a”, “an”,and “the” without any explicit indication of singularity ormultiplicity, this should be understood to mean that there is “at leastone” of the item, unless explicitly stated otherwise. When thesearticles are used in this way, the word describing the item(s) may bewritten in singular form and subsequent references to the item mayinclude the definite pronoun “the” for grammatical consistency, but thisdoes not necessarily mean that only one item is being referred to. Thus,for example, a phrase such as “an optical socket, wherein the opticalsocket . . . ” could encompass both one optical socket and multipleoptical sockets, notwithstanding the use of the singular form and thedefinite pronoun.

Occasionally the phrase “and/or” is used herein in conjunction with alist of items. This phrase means that any combination of items in thelist—from a single item to all of the items and any permutation inbetween—may be included. Thus, for example, “A, B, and/or C” means “oneof: {A}, {B}, {C}, {A, B}, {A, C}, {C, B}, and {A, C, B}”.

Various example processes were described above, with reference tovarious example flow charts. In the description and in the illustratedflow charts, operations are set forth in a particular order for ease ofdescription. However, it should be understood that some or all of theoperations could be performed in different orders than those describedand that some or all of the operations could be performed concurrently(i.e., in parallel).

While the above disclosure has been shown and described with referenceto the foregoing examples, it should be understood that other forms,details, and implementations may be made without departing from thespirit and scope of this disclosure.

What is claimed is:
 1. A system, comprising: a number of nodes, eachincluding a processor and a non-transitory machine readable mediumstoring a copy of an operating system image, wherein each copy of theoperating system image comprises: a minimum set of artifacts of a cloudplatform application; and lifecycle manager program instructions that,when executed by any of the nodes, instantiate a lifecycle manager forthe respective node that is to: in response to receiving a platformcluster creation request, automatically: establish a cloud platform ofthe cloud platform application including the respective node as a solemember; and invite others of the nodes to join the cloud platform; andin response to receiving an invitation to join an established cloudplatform of the cloud platform application that was established byanother one of the nodes, automatically integrate the respective nodeinto the established cloud platform.
 2. The system of claim 1, whereinthe lifecycle manager is to, in establishing the cloud platform,automatically establish a distributed key value cluster forcommunicating a state of the cloud platform among the nodes.
 3. Thesystem of claim 1, wherein the lifecycle manager is to, in integratingthe respective node into the established cloud platform, automaticallyjoin a distributed key value cluster associated with the establishedcloud platform.
 4. The system of claim 1, wherein the lifecycle manageris to, in integrating the respective node into the established cloudplatform, automatically determine which services of the cloud platformapplication to activate on the respective node based on a currentconfiguration of the established cloud platform.
 5. The system of claim1, wherein the lifecycle manager is to, in integrating the respectivenode into the established cloud platform, automatically: identify a rolefor the respective node based on the current configuration of theestablished cloud platform and a desired configuration, and select foractivation in the respective node those services of the cloud platformapplication that are associated with the identified role.
 6. The systemof claim 1 wherein the lifecycle manager is to, upon integrating intothe established cloud platform, automatically monitor for maintenancetasks to be performed and, in response to identifying a maintenance taskto be performed, attempt to reserve the maintenance task via adistributed key value store of the established cloud platform.
 7. Thesystem of claim 6, wherein the lifecycle manager is to, in monitoringfor maintenance tasks to be performed, automatically monitor a taskqueue of the established cloud platform for maintenance tasks that needto be performed.
 8. The system of claim 6, wherein the lifecycle manageris to, in monitoring for maintenance tasks to be performed,automatically monitor a status of the established cloud platform anddetect unplanned maintenance tasks based on the status of theestablished cloud platform.
 9. The system of claim 1, wherein thelifecycle manager is to monitor for scaling events and, in response todetecting a scaling event, automatically determine whether and how therespective node should reconfigure itself in view of the scaling event.10. The system of claim 1, wherein the lifecycle manager is to, uponintegrating into the established cloud platform, in response todetecting a change in a status of a given service of the establishedcloud platform, automatically determine whether the respective nodeshould take an action in view of the change in the status of the givenservice.
 11. A non-transitory machine readable medium storing anoperating system image comprising: a minimum set of artifacts of a cloudplatform application; and lifecycle manager program instructions that,when executed by a processor of a node, causes the node to instantiate alifecycle manager that is to: in response to receiving a cloud platformcreation request, automatically: establish a cloud platform of the cloudplatform application including the node as a sole member; and inviteother nodes to join the first cloud platform, in response to receivingan invitation to join an established cloud platform of the cloudplatform application, automatically integrate the node into theestablished cloud platform.
 12. The non-transitory machine readablemedium of claim 11, wherein the lifecycle manager is to, inautomatically integrating the node into the established cloud platform,automatically determine which services of the cloud platform applicationto activate on the respective node based on a current configuration ofthe established cloud platform.
 13. The non-transitory machine readablemedium of claim 11, wherein the lifecycle manager is to, in integratingthe node into the established cloud platform, automatically: identify arole for the node based on the current configuration of the establishedcloud platform and a desired configuration, and select for activation inthe node those services of the cloud platform application that areassociated with the identified role.
 14. The non-transitory machinereadable medium of claim 11, wherein the lifecycle manager is to, uponintegrating into the established cloud platform, automatically monitorfor maintenance tasks to be performed and, in response to identifying amaintenance task to be performed, attempt to reserve the maintenancetask via a distributed key value store of the established cloudplatform.
 15. The non-transitory machine readable medium of claim 11,wherein the lifecycle manager is to monitor for scaling events and, inresponse to detecting a scaling event, automatically determine whetherand how the respective node should reconfigure itself in view of thescaling event.
 16. A method, comprising: generating an operating systemimage that includes a minimum set of artifacts of a cloud platformapplication and machine readable instructions to instantiate a lifecyclemanager; install a copy of the operating system image on a number ofnodes, each comprising a processor and a non-transitory machine readablemedium; and send a cloud platform creation request to one of the nodes,wherein, for each of the nodes, the lifecycle manager is to: in responseto receiving the cloud platform creation request, automatically:establish a cloud platform of the cloud platform application includingthe respective node as a sole member; and invite others of the nodes tojoin the cloud platform; in response to receiving an invitation to joinan established cloud platform of the cloud platform application that wasestablished by another one of the nodes, automatically integrate therespective node into the established cloud platform.
 17. The method ofclaim 16, wherein the lifecycle manager is to, in automaticallyintegrating the node into the established cloud platform, automaticallydetermine which services of the cloud platform application to activateon the respective node based on a current configuration of theestablished cloud platform.
 18. The method of claim 16, wherein thelifecycle manager is to, in integrating the node into the establishedcloud platform, automatically: identify a role for the node based on thecurrent configuration of the established cloud platform and a desiredconfiguration, and select for activation in the node those services ofthe cloud platform application that are associated with the identifiedrole.
 19. The method of claim 16, wherein the lifecycle manager is to,upon integrating into the established cloud platform, automaticallymonitor for maintenance tasks to be performed and, in response toidentifying a maintenance task to be performed, attempt to reserve themaintenance task via a distributed key value store of the establishedcloud platform.
 20. The method of claim 16, wherein the lifecyclemanager is to monitor for scaling events and, in response to detecting ascaling event, automatically determine whether and how the respectivenode should reconfigure itself in view of the scaling event.